DESI Legacy Surveys and SDSS/BOSS Large Scale Structure

by Stéphanie Juneau, David Herrera, and the Astro Data Lab Team

Table of contents

Goals

Summary

In this Notebook, we explore large-scale structures of galaxies by combining spectroscopic redshifts from SDSS/BOSS with photometry from the DESI pre-imaging Legacy Survey (LS). The advantage of spectroscopic redshifts is that they are far more accurate than photometric redshifts to probe distances to galaxies (though still need to be corrected for possible distortion effects such as the finger-of-God effect, which we ignore here). The advantage of the LS photometry is that it reaches deeper than SDSS by about 1 magnitude, which yields better image quality to measure magnitudes, colors, and galaxy shapes. While there are several possible extensions to the example work included below, we will show that a simple figure of galaxy spatial locations color-coded by galaxy morphological type reveals the known morphology-density relation.

We wanted to extend indeed a little further and be able to visualize and even interact with a representation of these galaxies in the actual space. For that, we developed a 3D plot based directly (as a flat cube, without any projection or correction) on RA, DEC and z, and that is at the end of this NB.

On a technical point of view, this short notebook illustrates an example joint query between the LS DR10 photometry Tractor table, and the SDSS/BOSS DR17 specObj spectroscopy table. It uses a pre-crossmatched table based on the closest match within a 1.5 arcsec search radius.

The columns from the LS table used (Tractor) can be seen here: https://datalab.noirlab.edu/query.php?name=ls_dr10.tractor

The columns from the pre-crossmatched table can be seen here: https://datalab.noirlab.edu/query.php?name=ls_dr10.x1p5__tractor__sdss_dr17__specobj

The columns from the SDSS DR17 used for the 3D plot can be found here https://datalab.noirlab.edu/query.php?name=sdss_dr17.specobj

Disclaimer & attribution

If you use this notebook for your published science, please acknowledge the following:

Imports and setup

Please note that this notebook is written for Python 3.

Authentication

Much of the functionality of Data Lab can be accessed without explicitly logging in (the service then uses an anonymous login). But some capacities, for instance saving the results of your queries to your virtual storage space, require a login (i.e. you will need a registered user account).

If you need to log in to Data Lab, un-comment the cell below and execute it:

Query LS Tractor Photometry Catalog

The photometry is derived from Tractor modeling of sources, and the database includes model photometry, type (shape), as well as other quantities.

The Legacy Survey DR10 database is called ls_dr10 and includes several tables. We will use the tractor table together with the positional crossmatched table with specObj table from SDSS/BOSS DR17. The column names and descriptions can be found from the Data Lab Query Interface or using the Table Access Protocol (TAP) service with, e.g., TOPCAT.

The SDSS DR17 database is called sdss_dr17 and also includes several tables. We will use the specobj table, which has spectroscopic information.

Plot Results

Sanity check: RA, Dec positions from both tables

Visual Inspection of Large-Scale Structures

Plot the positions of a broad range of redshift, and overplot a thin slice in redshift to show possible structures within that slice.

Above, the left-hand panel shows a thin redshift slice (0.105 < z < 0.125, black symbols) among objects with redshifts from the spectroscopic SDSS DR13 sample (red symbols). We can see by eye some large-scale filamentary structures and overdensities. The blue rectangle shows a selected region where we zoom in the right-hand panel. On the latter, we further select a smaller region, which we will use in the next cell below.

The left-hand panel shows the small region enclosed in the blue rectangle that we chose above (right-hand panel). The galaxies in black are in the same narrow redshift slice as defined previously (0.105 < z < 0.125). The right-hand panel is an image cutout of the same region of the sky from the LS sky viewer. The galaxies encircled correspond to the points in black, and some or perhaps most of them likely belong to a galaxy cluster.

Large-Scale Structures with LS Morphologies

There are many possible extensions to this work. For instance, one could plot again with symbols coded with object type (from LS) and/or class (from SDSS) and/or velocity dispersion (from SDSS) and/or other quantities. Here, we will start with the object "TYPE" from LS, related to the morphological shapes.

The object shape (2D light profile) is modeled by the Tractor (Lang, Hogg & Mykytyn) as part of the procedure to compute model photometry.

Possible shapes for LS DR10 Morphological Classification:

Figure: Images of galaxies including a nearby elliptical galaxy, a nearby spiral galaxy, and a QSO.

EXERCISE: Large-Scale Structures with Galaxy Colors

There are pre-computed colors available. The columns are described here: https://datalab.noirlab.edu/query.php?name=ls_dr10.tractor

Another possibility would be to plot again the galaxies spatial coordinates, but color-coded according to their photometric colors. This is left as an exercise for the user, but feel free to get in touch with the Astro Data Lab Team if you have questions.

Large scale sctructure in 3D

We can explore filaments and clusters of galaxies better if we can plot them in 3D. We turn to a different area of the sky, and will query for a sample of SDSS galaxies in the near to slightly distant universe, and plot in 3D the cone containing them. To avoid conamination by the galactic plane of the Milky Way, we point our search cone at high galactic latitudes.

Data query and preparation

We select (mostly) SDSS galaxies within a 10-degree radius around a high galactic latitude direction, (ra,dec) = (160,45) degrees. We limit our search to positive redshifts between 0.02 and 0.3.

Run the query to fetch the SDSS data from the ls_dr17.specobj table

Reformat output into a table

Compute luminosity distance for every galaxy, using Planck2018 cosmology values

To plot the positions of each galaxy in true 3D space, we will convert the angular coordinates ra & dec, and the distance coordinate, to Cartesian coordinates X,Y,Z (all measured in Mpc from the coordinate system origin).

Plotting in 3D

To create an interactive 3D plot (one where we can zoom, pan, and rotate the scene), we will use the plotly package. The galaxies in our sample will be plotted using a 3D scatter routine. We also set some overall properties of the plot, such as the size of the markers, and a color map (we color each galaxy redder the further away it is).

Next, we define camera location and the layout of the plot

Explore the scene by:

Observe how the galaxies form compact groups and clusters, and on larger scales form huge filaments. This is the large scale structure of the universe. In details, we can also notice some elongation along the direction of redshift, which is sometimes called the "Fingers of God" effect. This is due to additional contributions to the redshift coming from the proper motions of galaxies. This effect is usually corrected in a statistical manner rather than on a galaxy-per-galaxy basis (other useful explainer).